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Harrison/official pre release (#8106)
This commit is contained in:
Harrison Chase
GitHub
4
libs/experimental/langchain_experimental/sql/__init__.py
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4
libs/experimental/langchain_experimental/sql/__init__.py
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@@ -0,0 +1,4 @@
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"""Chain for interacting with SQL Database."""
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from langchain_experimental.sql.base import SQLDatabaseChain
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__all__ = ["SQLDatabaseChain"]
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291
libs/experimental/langchain_experimental/sql/base.py
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291
libs/experimental/langchain_experimental/sql/base.py
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@@ -0,0 +1,291 @@
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"""Chain for interacting with SQL Database."""
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from __future__ import annotations
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import warnings
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from typing import Any, Dict, List, Optional
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from langchain.callbacks.manager import CallbackManagerForChainRun
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from langchain.chains.base import Chain
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from langchain.chains.llm import LLMChain
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from langchain.prompts.prompt import PromptTemplate
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from langchain.schema import BasePromptTemplate
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from langchain.schema.language_model import BaseLanguageModel
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from langchain.tools.sql_database.prompt import QUERY_CHECKER
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from langchain.utilities.sql_database import SQLDatabase
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from pydantic import Extra, Field, root_validator
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from langchain_experimental.sql.prompt import DECIDER_PROMPT, PROMPT, SQL_PROMPTS
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INTERMEDIATE_STEPS_KEY = "intermediate_steps"
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class SQLDatabaseChain(Chain):
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"""Chain for interacting with SQL Database.
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Example:
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.. code-block:: python
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from langchain_experimental.sql import SQLDatabaseChain
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from langchain import OpenAI, SQLDatabase
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db = SQLDatabase(...)
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db_chain = SQLDatabaseChain.from_llm(OpenAI(), db)
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"""
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llm_chain: LLMChain
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llm: Optional[BaseLanguageModel] = None
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"""[Deprecated] LLM wrapper to use."""
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database: SQLDatabase = Field(exclude=True)
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"""SQL Database to connect to."""
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prompt: Optional[BasePromptTemplate] = None
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"""[Deprecated] Prompt to use to translate natural language to SQL."""
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top_k: int = 5
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"""Number of results to return from the query"""
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input_key: str = "query" #: :meta private:
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output_key: str = "result" #: :meta private:
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return_sql: bool = False
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"""Will return sql-command directly without executing it"""
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return_intermediate_steps: bool = False
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"""Whether or not to return the intermediate steps along with the final answer."""
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return_direct: bool = False
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"""Whether or not to return the result of querying the SQL table directly."""
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use_query_checker: bool = False
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"""Whether or not the query checker tool should be used to attempt
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to fix the initial SQL from the LLM."""
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query_checker_prompt: Optional[BasePromptTemplate] = None
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"""The prompt template that should be used by the query checker"""
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class Config:
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"""Configuration for this pydantic object."""
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extra = Extra.forbid
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arbitrary_types_allowed = True
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@root_validator(pre=True)
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def raise_deprecation(cls, values: Dict) -> Dict:
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if "llm" in values:
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warnings.warn(
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"Directly instantiating an SQLDatabaseChain with an llm is deprecated. "
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"Please instantiate with llm_chain argument or using the from_llm "
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"class method."
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)
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if "llm_chain" not in values and values["llm"] is not None:
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database = values["database"]
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prompt = values.get("prompt") or SQL_PROMPTS.get(
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database.dialect, PROMPT
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)
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values["llm_chain"] = LLMChain(llm=values["llm"], prompt=prompt)
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return values
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@property
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def input_keys(self) -> List[str]:
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"""Return the singular input key.
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:meta private:
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"""
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return [self.input_key]
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@property
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def output_keys(self) -> List[str]:
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"""Return the singular output key.
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:meta private:
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"""
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if not self.return_intermediate_steps:
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return [self.output_key]
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else:
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return [self.output_key, INTERMEDIATE_STEPS_KEY]
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def _call(
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self,
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inputs: Dict[str, Any],
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run_manager: Optional[CallbackManagerForChainRun] = None,
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) -> Dict[str, Any]:
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_run_manager = run_manager or CallbackManagerForChainRun.get_noop_manager()
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input_text = f"{inputs[self.input_key]}\nSQLQuery:"
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_run_manager.on_text(input_text, verbose=self.verbose)
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# If not present, then defaults to None which is all tables.
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table_names_to_use = inputs.get("table_names_to_use")
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table_info = self.database.get_table_info(table_names=table_names_to_use)
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llm_inputs = {
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"input": input_text,
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"top_k": str(self.top_k),
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"dialect": self.database.dialect,
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"table_info": table_info,
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"stop": ["\nSQLResult:"],
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}
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intermediate_steps: List = []
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try:
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intermediate_steps.append(llm_inputs) # input: sql generation
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sql_cmd = self.llm_chain.predict(
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callbacks=_run_manager.get_child(),
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**llm_inputs,
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).strip()
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if self.return_sql:
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return {self.output_key: sql_cmd}
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if not self.use_query_checker:
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_run_manager.on_text(sql_cmd, color="green", verbose=self.verbose)
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intermediate_steps.append(
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sql_cmd
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) # output: sql generation (no checker)
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intermediate_steps.append({"sql_cmd": sql_cmd}) # input: sql exec
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result = self.database.run(sql_cmd)
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intermediate_steps.append(str(result)) # output: sql exec
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else:
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query_checker_prompt = self.query_checker_prompt or PromptTemplate(
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template=QUERY_CHECKER, input_variables=["query", "dialect"]
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)
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query_checker_chain = LLMChain(
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llm=self.llm_chain.llm, prompt=query_checker_prompt
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)
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query_checker_inputs = {
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"query": sql_cmd,
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"dialect": self.database.dialect,
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}
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checked_sql_command: str = query_checker_chain.predict(
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callbacks=_run_manager.get_child(), **query_checker_inputs
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).strip()
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intermediate_steps.append(
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checked_sql_command
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) # output: sql generation (checker)
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_run_manager.on_text(
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checked_sql_command, color="green", verbose=self.verbose
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)
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intermediate_steps.append(
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{"sql_cmd": checked_sql_command}
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) # input: sql exec
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result = self.database.run(checked_sql_command)
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intermediate_steps.append(str(result)) # output: sql exec
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sql_cmd = checked_sql_command
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_run_manager.on_text("\nSQLResult: ", verbose=self.verbose)
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_run_manager.on_text(result, color="yellow", verbose=self.verbose)
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# If return direct, we just set the final result equal to
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# the result of the sql query result, otherwise try to get a human readable
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# final answer
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if self.return_direct:
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final_result = result
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else:
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_run_manager.on_text("\nAnswer:", verbose=self.verbose)
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input_text += f"{sql_cmd}\nSQLResult: {result}\nAnswer:"
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llm_inputs["input"] = input_text
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intermediate_steps.append(llm_inputs) # input: final answer
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final_result = self.llm_chain.predict(
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callbacks=_run_manager.get_child(),
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**llm_inputs,
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).strip()
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intermediate_steps.append(final_result) # output: final answer
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_run_manager.on_text(final_result, color="green", verbose=self.verbose)
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chain_result: Dict[str, Any] = {self.output_key: final_result}
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if self.return_intermediate_steps:
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chain_result[INTERMEDIATE_STEPS_KEY] = intermediate_steps
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return chain_result
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except Exception as exc:
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# Append intermediate steps to exception, to aid in logging and later
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# improvement of few shot prompt seeds
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exc.intermediate_steps = intermediate_steps # type: ignore
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raise exc
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@property
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def _chain_type(self) -> str:
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return "sql_database_chain"
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@classmethod
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def from_llm(
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cls,
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llm: BaseLanguageModel,
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db: SQLDatabase,
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prompt: Optional[BasePromptTemplate] = None,
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**kwargs: Any,
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) -> SQLDatabaseChain:
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prompt = prompt or SQL_PROMPTS.get(db.dialect, PROMPT)
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llm_chain = LLMChain(llm=llm, prompt=prompt)
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return cls(llm_chain=llm_chain, database=db, **kwargs)
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class SQLDatabaseSequentialChain(Chain):
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"""Chain for querying SQL database that is a sequential chain.
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The chain is as follows:
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1. Based on the query, determine which tables to use.
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2. Based on those tables, call the normal SQL database chain.
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This is useful in cases where the number of tables in the database is large.
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"""
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decider_chain: LLMChain
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sql_chain: SQLDatabaseChain
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input_key: str = "query" #: :meta private:
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output_key: str = "result" #: :meta private:
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return_intermediate_steps: bool = False
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@classmethod
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def from_llm(
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cls,
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llm: BaseLanguageModel,
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database: SQLDatabase,
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query_prompt: BasePromptTemplate = PROMPT,
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decider_prompt: BasePromptTemplate = DECIDER_PROMPT,
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**kwargs: Any,
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) -> SQLDatabaseSequentialChain:
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"""Load the necessary chains."""
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sql_chain = SQLDatabaseChain.from_llm(
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llm, database, prompt=query_prompt, **kwargs
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)
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decider_chain = LLMChain(
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llm=llm, prompt=decider_prompt, output_key="table_names"
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)
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return cls(sql_chain=sql_chain, decider_chain=decider_chain, **kwargs)
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@property
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def input_keys(self) -> List[str]:
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"""Return the singular input key.
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:meta private:
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"""
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return [self.input_key]
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@property
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def output_keys(self) -> List[str]:
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"""Return the singular output key.
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:meta private:
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"""
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if not self.return_intermediate_steps:
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return [self.output_key]
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else:
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return [self.output_key, INTERMEDIATE_STEPS_KEY]
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def _call(
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self,
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inputs: Dict[str, Any],
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run_manager: Optional[CallbackManagerForChainRun] = None,
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) -> Dict[str, Any]:
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_run_manager = run_manager or CallbackManagerForChainRun.get_noop_manager()
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_table_names = self.sql_chain.database.get_usable_table_names()
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table_names = ", ".join(_table_names)
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llm_inputs = {
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"query": inputs[self.input_key],
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"table_names": table_names,
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}
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_lowercased_table_names = [name.lower() for name in _table_names]
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table_names_from_chain = self.decider_chain.predict_and_parse(**llm_inputs)
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table_names_to_use = [
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name
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for name in table_names_from_chain
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if name.lower() in _lowercased_table_names
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]
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_run_manager.on_text("Table names to use:", end="\n", verbose=self.verbose)
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_run_manager.on_text(
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str(table_names_to_use), color="yellow", verbose=self.verbose
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)
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new_inputs = {
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self.sql_chain.input_key: inputs[self.input_key],
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"table_names_to_use": table_names_to_use,
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}
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return self.sql_chain(
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new_inputs, callbacks=_run_manager.get_child(), return_only_outputs=True
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)
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@property
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def _chain_type(self) -> str:
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return "sql_database_sequential_chain"
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263
libs/experimental/langchain_experimental/sql/prompt.py
Normal file
263
libs/experimental/langchain_experimental/sql/prompt.py
Normal file
@@ -0,0 +1,263 @@
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# flake8: noqa
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from langchain.output_parsers.list import CommaSeparatedListOutputParser
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from langchain.prompts.prompt import PromptTemplate
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PROMPT_SUFFIX = """Only use the following tables:
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{table_info}
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Question: {input}"""
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_DEFAULT_TEMPLATE = """Given an input question, first create a syntactically correct {dialect} query to run, then look at the results of the query and return the answer. Unless the user specifies in his question a specific number of examples he wishes to obtain, always limit your query to at most {top_k} results. You can order the results by a relevant column to return the most interesting examples in the database.
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Never query for all the columns from a specific table, only ask for a the few relevant columns given the question.
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Pay attention to use only the column names that you can see in the schema description. Be careful to not query for columns that do not exist. Also, pay attention to which column is in which table.
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Use the following format:
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Question: Question here
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SQLQuery: SQL Query to run
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SQLResult: Result of the SQLQuery
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Answer: Final answer here
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"""
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PROMPT = PromptTemplate(
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input_variables=["input", "table_info", "dialect", "top_k"],
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template=_DEFAULT_TEMPLATE + PROMPT_SUFFIX,
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)
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_DECIDER_TEMPLATE = """Given the below input question and list of potential tables, output a comma separated list of the table names that may be necessary to answer this question.
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Question: {query}
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Table Names: {table_names}
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Relevant Table Names:"""
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DECIDER_PROMPT = PromptTemplate(
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input_variables=["query", "table_names"],
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template=_DECIDER_TEMPLATE,
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output_parser=CommaSeparatedListOutputParser(),
|
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)
|
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_duckdb_prompt = """You are a DuckDB expert. Given an input question, first create a syntactically correct DuckDB query to run, then look at the results of the query and return the answer to the input question.
|
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Unless the user specifies in the question a specific number of examples to obtain, query for at most {top_k} results using the LIMIT clause as per DuckDB. You can order the results to return the most informative data in the database.
|
||||
Never query for all columns from a table. You must query only the columns that are needed to answer the question. Wrap each column name in double quotes (") to denote them as delimited identifiers.
|
||||
Pay attention to use only the column names you can see in the tables below. Be careful to not query for columns that do not exist. Also, pay attention to which column is in which table.
|
||||
Pay attention to use today() function to get the current date, if the question involves "today".
|
||||
|
||||
Use the following format:
|
||||
|
||||
Question: Question here
|
||||
SQLQuery: SQL Query to run
|
||||
SQLResult: Result of the SQLQuery
|
||||
Answer: Final answer here
|
||||
|
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"""
|
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|
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DUCKDB_PROMPT = PromptTemplate(
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input_variables=["input", "table_info", "top_k"],
|
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template=_duckdb_prompt + PROMPT_SUFFIX,
|
||||
)
|
||||
|
||||
_googlesql_prompt = """You are a GoogleSQL expert. Given an input question, first create a syntactically correct GoogleSQL query to run, then look at the results of the query and return the answer to the input question.
|
||||
Unless the user specifies in the question a specific number of examples to obtain, query for at most {top_k} results using the LIMIT clause as per GoogleSQL. You can order the results to return the most informative data in the database.
|
||||
Never query for all columns from a table. You must query only the columns that are needed to answer the question. Wrap each column name in backticks (`) to denote them as delimited identifiers.
|
||||
Pay attention to use only the column names you can see in the tables below. Be careful to not query for columns that do not exist. Also, pay attention to which column is in which table.
|
||||
Pay attention to use CURRENT_DATE() function to get the current date, if the question involves "today".
|
||||
|
||||
Use the following format:
|
||||
|
||||
Question: Question here
|
||||
SQLQuery: SQL Query to run
|
||||
SQLResult: Result of the SQLQuery
|
||||
Answer: Final answer here
|
||||
|
||||
"""
|
||||
|
||||
GOOGLESQL_PROMPT = PromptTemplate(
|
||||
input_variables=["input", "table_info", "top_k"],
|
||||
template=_googlesql_prompt + PROMPT_SUFFIX,
|
||||
)
|
||||
|
||||
|
||||
_mssql_prompt = """You are an MS SQL expert. Given an input question, first create a syntactically correct MS SQL query to run, then look at the results of the query and return the answer to the input question.
|
||||
Unless the user specifies in the question a specific number of examples to obtain, query for at most {top_k} results using the TOP clause as per MS SQL. You can order the results to return the most informative data in the database.
|
||||
Never query for all columns from a table. You must query only the columns that are needed to answer the question. Wrap each column name in square brackets ([]) to denote them as delimited identifiers.
|
||||
Pay attention to use only the column names you can see in the tables below. Be careful to not query for columns that do not exist. Also, pay attention to which column is in which table.
|
||||
Pay attention to use CAST(GETDATE() as date) function to get the current date, if the question involves "today".
|
||||
|
||||
Use the following format:
|
||||
|
||||
Question: Question here
|
||||
SQLQuery: SQL Query to run
|
||||
SQLResult: Result of the SQLQuery
|
||||
Answer: Final answer here
|
||||
|
||||
"""
|
||||
|
||||
MSSQL_PROMPT = PromptTemplate(
|
||||
input_variables=["input", "table_info", "top_k"],
|
||||
template=_mssql_prompt + PROMPT_SUFFIX,
|
||||
)
|
||||
|
||||
|
||||
_mysql_prompt = """You are a MySQL expert. Given an input question, first create a syntactically correct MySQL query to run, then look at the results of the query and return the answer to the input question.
|
||||
Unless the user specifies in the question a specific number of examples to obtain, query for at most {top_k} results using the LIMIT clause as per MySQL. You can order the results to return the most informative data in the database.
|
||||
Never query for all columns from a table. You must query only the columns that are needed to answer the question. Wrap each column name in backticks (`) to denote them as delimited identifiers.
|
||||
Pay attention to use only the column names you can see in the tables below. Be careful to not query for columns that do not exist. Also, pay attention to which column is in which table.
|
||||
Pay attention to use CURDATE() function to get the current date, if the question involves "today".
|
||||
|
||||
Use the following format:
|
||||
|
||||
Question: Question here
|
||||
SQLQuery: SQL Query to run
|
||||
SQLResult: Result of the SQLQuery
|
||||
Answer: Final answer here
|
||||
|
||||
"""
|
||||
|
||||
MYSQL_PROMPT = PromptTemplate(
|
||||
input_variables=["input", "table_info", "top_k"],
|
||||
template=_mysql_prompt + PROMPT_SUFFIX,
|
||||
)
|
||||
|
||||
|
||||
_mariadb_prompt = """You are a MariaDB expert. Given an input question, first create a syntactically correct MariaDB query to run, then look at the results of the query and return the answer to the input question.
|
||||
Unless the user specifies in the question a specific number of examples to obtain, query for at most {top_k} results using the LIMIT clause as per MariaDB. You can order the results to return the most informative data in the database.
|
||||
Never query for all columns from a table. You must query only the columns that are needed to answer the question. Wrap each column name in backticks (`) to denote them as delimited identifiers.
|
||||
Pay attention to use only the column names you can see in the tables below. Be careful to not query for columns that do not exist. Also, pay attention to which column is in which table.
|
||||
Pay attention to use CURDATE() function to get the current date, if the question involves "today".
|
||||
|
||||
Use the following format:
|
||||
|
||||
Question: Question here
|
||||
SQLQuery: SQL Query to run
|
||||
SQLResult: Result of the SQLQuery
|
||||
Answer: Final answer here
|
||||
|
||||
"""
|
||||
|
||||
MARIADB_PROMPT = PromptTemplate(
|
||||
input_variables=["input", "table_info", "top_k"],
|
||||
template=_mariadb_prompt + PROMPT_SUFFIX,
|
||||
)
|
||||
|
||||
|
||||
_oracle_prompt = """You are an Oracle SQL expert. Given an input question, first create a syntactically correct Oracle SQL query to run, then look at the results of the query and return the answer to the input question.
|
||||
Unless the user specifies in the question a specific number of examples to obtain, query for at most {top_k} results using the FETCH FIRST n ROWS ONLY clause as per Oracle SQL. You can order the results to return the most informative data in the database.
|
||||
Never query for all columns from a table. You must query only the columns that are needed to answer the question. Wrap each column name in double quotes (") to denote them as delimited identifiers.
|
||||
Pay attention to use only the column names you can see in the tables below. Be careful to not query for columns that do not exist. Also, pay attention to which column is in which table.
|
||||
Pay attention to use TRUNC(SYSDATE) function to get the current date, if the question involves "today".
|
||||
|
||||
Use the following format:
|
||||
|
||||
Question: Question here
|
||||
SQLQuery: SQL Query to run
|
||||
SQLResult: Result of the SQLQuery
|
||||
Answer: Final answer here
|
||||
|
||||
"""
|
||||
|
||||
ORACLE_PROMPT = PromptTemplate(
|
||||
input_variables=["input", "table_info", "top_k"],
|
||||
template=_oracle_prompt + PROMPT_SUFFIX,
|
||||
)
|
||||
|
||||
|
||||
_postgres_prompt = """You are a PostgreSQL expert. Given an input question, first create a syntactically correct PostgreSQL query to run, then look at the results of the query and return the answer to the input question.
|
||||
Unless the user specifies in the question a specific number of examples to obtain, query for at most {top_k} results using the LIMIT clause as per PostgreSQL. You can order the results to return the most informative data in the database.
|
||||
Never query for all columns from a table. You must query only the columns that are needed to answer the question. Wrap each column name in double quotes (") to denote them as delimited identifiers.
|
||||
Pay attention to use only the column names you can see in the tables below. Be careful to not query for columns that do not exist. Also, pay attention to which column is in which table.
|
||||
Pay attention to use CURRENT_DATE function to get the current date, if the question involves "today".
|
||||
|
||||
Use the following format:
|
||||
|
||||
Question: Question here
|
||||
SQLQuery: SQL Query to run
|
||||
SQLResult: Result of the SQLQuery
|
||||
Answer: Final answer here
|
||||
|
||||
"""
|
||||
|
||||
POSTGRES_PROMPT = PromptTemplate(
|
||||
input_variables=["input", "table_info", "top_k"],
|
||||
template=_postgres_prompt + PROMPT_SUFFIX,
|
||||
)
|
||||
|
||||
|
||||
_sqlite_prompt = """You are a SQLite expert. Given an input question, first create a syntactically correct SQLite query to run, then look at the results of the query and return the answer to the input question.
|
||||
Unless the user specifies in the question a specific number of examples to obtain, query for at most {top_k} results using the LIMIT clause as per SQLite. You can order the results to return the most informative data in the database.
|
||||
Never query for all columns from a table. You must query only the columns that are needed to answer the question. Wrap each column name in double quotes (") to denote them as delimited identifiers.
|
||||
Pay attention to use only the column names you can see in the tables below. Be careful to not query for columns that do not exist. Also, pay attention to which column is in which table.
|
||||
Pay attention to use date('now') function to get the current date, if the question involves "today".
|
||||
|
||||
Use the following format:
|
||||
|
||||
Question: Question here
|
||||
SQLQuery: SQL Query to run
|
||||
SQLResult: Result of the SQLQuery
|
||||
Answer: Final answer here
|
||||
|
||||
"""
|
||||
|
||||
SQLITE_PROMPT = PromptTemplate(
|
||||
input_variables=["input", "table_info", "top_k"],
|
||||
template=_sqlite_prompt + PROMPT_SUFFIX,
|
||||
)
|
||||
|
||||
_clickhouse_prompt = """You are a ClickHouse expert. Given an input question, first create a syntactically correct Clic query to run, then look at the results of the query and return the answer to the input question.
|
||||
Unless the user specifies in the question a specific number of examples to obtain, query for at most {top_k} results using the LIMIT clause as per ClickHouse. You can order the results to return the most informative data in the database.
|
||||
Never query for all columns from a table. You must query only the columns that are needed to answer the question. Wrap each column name in double quotes (") to denote them as delimited identifiers.
|
||||
Pay attention to use only the column names you can see in the tables below. Be careful to not query for columns that do not exist. Also, pay attention to which column is in which table.
|
||||
Pay attention to use today() function to get the current date, if the question involves "today".
|
||||
|
||||
Use the following format:
|
||||
|
||||
Question: "Question here"
|
||||
SQLQuery: "SQL Query to run"
|
||||
SQLResult: "Result of the SQLQuery"
|
||||
Answer: "Final answer here"
|
||||
|
||||
"""
|
||||
|
||||
CLICKHOUSE_PROMPT = PromptTemplate(
|
||||
input_variables=["input", "table_info", "top_k"],
|
||||
template=_clickhouse_prompt + PROMPT_SUFFIX,
|
||||
)
|
||||
|
||||
_prestodb_prompt = """You are a PrestoDB expert. Given an input question, first create a syntactically correct PrestoDB query to run, then look at the results of the query and return the answer to the input question.
|
||||
Unless the user specifies in the question a specific number of examples to obtain, query for at most {top_k} results using the LIMIT clause as per PrestoDB. You can order the results to return the most informative data in the database.
|
||||
Never query for all columns from a table. You must query only the columns that are needed to answer the question. Wrap each column name in double quotes (") to denote them as delimited identifiers.
|
||||
Pay attention to use only the column names you can see in the tables below. Be careful to not query for columns that do not exist. Also, pay attention to which column is in which table.
|
||||
Pay attention to use current_date function to get the current date, if the question involves "today".
|
||||
|
||||
Use the following format:
|
||||
|
||||
Question: "Question here"
|
||||
SQLQuery: "SQL Query to run"
|
||||
SQLResult: "Result of the SQLQuery"
|
||||
Answer: "Final answer here"
|
||||
|
||||
"""
|
||||
|
||||
PRESTODB_PROMPT = PromptTemplate(
|
||||
input_variables=["input", "table_info", "top_k"],
|
||||
template=_prestodb_prompt + PROMPT_SUFFIX,
|
||||
)
|
||||
|
||||
|
||||
SQL_PROMPTS = {
|
||||
"duckdb": DUCKDB_PROMPT,
|
||||
"googlesql": GOOGLESQL_PROMPT,
|
||||
"mssql": MSSQL_PROMPT,
|
||||
"mysql": MYSQL_PROMPT,
|
||||
"mariadb": MARIADB_PROMPT,
|
||||
"oracle": ORACLE_PROMPT,
|
||||
"postgresql": POSTGRES_PROMPT,
|
||||
"sqlite": SQLITE_PROMPT,
|
||||
"clickhouse": CLICKHOUSE_PROMPT,
|
||||
"prestodb": PRESTODB_PROMPT,
|
||||
}
|
||||
Reference in New Issue
Block a user